WO2015145625A1 - Dispositif, procede et programme d'estimation d'etat corporel - Google Patents

Dispositif, procede et programme d'estimation d'etat corporel Download PDF

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WO2015145625A1
WO2015145625A1 PCT/JP2014/058589 JP2014058589W WO2015145625A1 WO 2015145625 A1 WO2015145625 A1 WO 2015145625A1 JP 2014058589 W JP2014058589 W JP 2014058589W WO 2015145625 A1 WO2015145625 A1 WO 2015145625A1
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Prior art keywords
signal
rotation angle
biological state
electrocardiogram
estimated
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PCT/JP2014/058589
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English (en)
Japanese (ja)
Inventor
芳孝 木村
伸生 八重樫
州博 岡村
拓哉 伊藤
邦博 小出
美雪 遠藤
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国立大学法人東北大学
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Priority to PCT/JP2014/058589 priority Critical patent/WO2015145625A1/fr
Priority to JP2016509717A priority patent/JP6359084B2/ja
Publication of WO2015145625A1 publication Critical patent/WO2015145625A1/fr
Priority to US15/273,976 priority patent/US10631773B2/en

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/43—Detecting, measuring or recording for evaluating the reproductive systems
    • A61B5/4306—Detecting, measuring or recording for evaluating the reproductive systems for evaluating the female reproductive systems, e.g. gynaecological evaluations
    • A61B5/4343—Pregnancy and labour monitoring, e.g. for labour onset detection
    • A61B5/4362—Assessing foetal parameters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02411—Detecting, measuring or recording pulse rate or heart rate of foetuses
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1118—Determining activity level
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/344—Foetal cardiography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/347—Detecting the frequency distribution of signals
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/352—Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
    • A61B5/316—Modalities, i.e. specific diagnostic methods
    • A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
    • A61B5/346—Analysis of electrocardiograms
    • A61B5/349—Detecting specific parameters of the electrocardiograph cycle
    • A61B5/366—Detecting abnormal QRS complex, e.g. widening

Definitions

  • the present invention relates to a biological state estimation device, a biological state estimation method, and a biological state estimation program.
  • An electrocardiogram signal representing a change in electromotive force is estimated by measuring a potential signal representing a change in potential on the surface via an electrode attached to the surface of the living body.
  • the electrocardiogram signal includes a wave having a peak called a P wave WP, a Q wave WQ, an R wave WR, an S wave WS, and a T wave WT for each beat.
  • the time interval between the peaks of each wave is used for disease diagnosis or examination.
  • the heart rate is measured by acquiring the time interval between the peaks of the continuous R wave WR.
  • a biological state estimation device that acquires information representing a biological state is known.
  • the biological state estimation device described in Patent Document 1 acquires an RR interval that is a time interval between successive R wave peaks based on an electrocardiogram signal of the biological body. Furthermore, the biological state estimating device calculates an average value of the acquired RR intervals.
  • the biological state estimating apparatus calculates a first parameter based on a deviation from the average value for each of the RR intervals smaller than the average value among the acquired RR intervals. Furthermore, the biological state estimating device calculates a second parameter based on a deviation from the average value for each of the RR intervals larger than the average value among the acquired RR intervals. Then, the biological state estimation device acquires the ratio of the first parameter and the second parameter as information representing the asymmetry of the RR interval.
  • the ratio of the first parameter and the second parameter may be the same in two states where the probability distribution of the RR interval is relatively different.
  • the ratio between the first parameter and the second parameter may not represent the probability distribution of the RR interval with sufficiently high accuracy. Therefore, there is a possibility that the biological state estimation apparatus cannot acquire information that represents the state of the biological body with high accuracy.
  • One of the objects of the present invention is to solve the above-described problem that information indicating the state of a living body with high accuracy may not be obtained.
  • the living body state estimation device acquires information representing the state of the living body.
  • the biological state estimation device includes an electrocardiogram signal acquisition unit that acquires an electrocardiogram signal of the living body, and a probability distribution with respect to a reference wave interval that is a time interval between peaks of a predetermined reference wave that is continuous in the acquired electrocardiogram signal.
  • An information acquisition unit that acquires, as the information, a parameter that specifies a predetermined function that represents
  • the biological state estimation method acquires information representing a biological state. Further, the biological state estimation method acquires an electrocardiogram signal of the living body, and a predetermined function representing a probability distribution with respect to a reference wave interval that is a time interval between peaks of a predetermined reference wave continuous in the acquired electrocardiogram signal. Is acquired as the above information.
  • the biological state estimation program is a program for causing a computer to execute a process of acquiring information representing a biological state. Furthermore, the biological state estimation program acquires the electrocardiogram signal of the living body to the computer, and obtains a probability distribution with respect to a reference wave interval that is a time interval between successive peaks of a predetermined reference wave in the acquired electrocardiogram signal. A process for acquiring a parameter specifying a predetermined function to be expressed as the information is executed.
  • information representing the biological state with high accuracy can be acquired.
  • the fetal state estimation device 1 includes a measurement unit 10, a processing unit 20, and an output unit 30.
  • the fetal state estimation device 1 is an example of a biological state estimation device.
  • the measurement unit 10 includes electrodes 11 to 15. 2 shows an example in which the measurement unit 10 includes five electrodes. However, the number of electrodes included in the measurement unit 10 may be four or less, or may be six or more. Good. Each electrode 11-15 is attached to the abdominal surface (eg skin) MBS of the maternal MB during pregnancy.
  • the measurement unit 10 measures a biopotential signal representing a change in potential on the surface MBS of the mother MB via the electrodes 11 to 15.
  • the bioelectric potential signal includes a maternal electrocardiogram basic signal caused by the heart beat of the mother MB, a maternal electromyogram basic signal caused by the activity of the muscle fiber of the mother MB, and the heart of the fetus CB housed in the uterus of the mother MB. This is a signal in which a basic fetal electrocardiogram signal, noise, and the like resulting from pulsation are superimposed.
  • the processing unit 20 processes the biopotential signal measured by the measuring unit 10. As illustrated in FIG. 3, the function of the processing unit 20 includes an electrocardiogram signal acquisition unit 210, an information acquisition unit 220, and a biological state determination unit 230.
  • the processing unit 20 includes a processing device (for example, a CPU (Central Processing Unit) or DSP (Digital Signal Processor)) and a storage device, and a fetal state estimation program stored in advance in the storage device. Each function is realized by executing. Note that the processing unit 20 may realize at least a part of the functions by an integrated circuit (for example, LSI (Large Scale Integration)).
  • LSI Large Scale Integration
  • the electrocardiogram signal acquisition unit 210 acquires the electrocardiogram signal of the fetus CB in the mother MB based on the biopotential signal measured by the measurement unit 10.
  • the electrocardiogram signal acquisition unit 210 includes a rotation angle estimation unit 211 and an electrocardiogram signal estimation unit 212.
  • the rotation angle estimation unit 211 extracts a fetal electrocardiogram basic signal from the bioelectric potential signal measured by the measurement unit 10 by using an independent component analysis (ICA) method.
  • ICA independent component analysis
  • the ICA method is a natural gradient method, a FastICA method, or a reference system ICA method.
  • the reference system ICA method generates a reference signal based on a heartbeat period signal that represents the period of the heartbeat of the fetus, A fetal electrocardiogram basic signal is extracted from a biopotential signal based on the bioelectric potential signal.
  • the heartbeat cycle signal may be generated based on the biopotential signal.
  • the heartbeat cycle signal may be a signal measured by an ultrasonic sensor.
  • the rotation angle estimation unit 211 may extract the fetal electrocardiogram basic signal after performing a reduction process for reducing the maternal electrocardiogram basic signal on the measured bioelectric potential signal.
  • the rotation angle estimation unit 211 estimates the maternal electrocardiogram basic signal via an electrode (not shown) attached to the chest of the maternal MB, and performs the reduction process based on the estimated maternal electrocardiogram basic signal. May be executed.
  • the rotation angle estimation unit 211 may extract a fetal electrocardiogram basic signal after reducing noise by applying a bandpass filter.
  • the rotation angle estimation unit 211 may use a band pass filter having a band from 20 Hz to 30 Hz as a pass band.
  • FIG. 4 shows two biopotential signals C10 and C11 measured in two states in which the positions of the electrodes with respect to the heart are different from each other when the changes in electromotive force are the same. For example, as shown in FIG. 4, the magnitude and timing of the peak of each wave change according to the position of the electrode with respect to the heart.
  • the fetus CB rotates with respect to the mother MB in a relatively short time. Therefore, with the rotation of the fetus CB, in the biopotential signal measured through the electrodes 11 to 15 attached to the surface MBS of the mother MB, the manner in which the change in the electromotive force of the fetus CB appears easily changes.
  • the fetal state estimation device 1 estimates the rotation angle of the fetus CB relative to the mother MB, and based on the estimated rotation angle, the fetal CB electrocardiogram signal (fetal electrocardiogram) with respect to a predetermined reference rotation angle. Signal).
  • the fetal electrocardiogram signal fetal electrocardiogram
  • the manner in which changes in the electromotive force of the fetus CB appear is constant. Therefore, information representing the state of the fetus CB with high accuracy can be acquired based on the fetal electrocardiogram signal.
  • the rotation angle estimation unit 211 estimates the rotation angle of the fetus CB with respect to the mother MB based on the extracted fetal electrocardiogram basic signal. Hereinafter, estimation of the rotation angle will be described.
  • a right-handed orthogonal coordinate system is used as shown in FIG.
  • This orthogonal coordinate system has the front direction of the fetus CB as the y-axis, the lower direction of the fetus CB as the z-axis, and the left direction of the fetus CB as the x-axis.
  • the rotation angle ⁇ with respect to the fetus CB is an angle rotated counterclockwise from the x axis when the fetus CB is viewed in the positive direction of the z axis.
  • the rotational movement of the fetus CB is a movement that rotates about the direction along the z axis as the central axis of rotation.
  • the fetal state estimation device 1 may be applied when the vertical direction of the fetus CB is different from the vertical direction of the mother MB.
  • ECG ⁇ ( ⁇ ) when the fetus CB is viewed in the direction in which the negative direction of the x-axis is rotated by the rotation angle ⁇ is expressed as Equation 1.
  • the ⁇ represents time.
  • the fetal electrocardiogram signal ECG x ( ⁇ ) may be regarded as a signal representing an electrocardiogram obtained by projecting the vector electrocardiogram onto the left side surface of the fetus CB.
  • the fetal electrocardiogram signal ECG y ( ⁇ ) may be regarded as a signal representing an electrocardiogram obtained by projecting a vector electrocardiogram onto the front of the fetus CB.
  • the fetal electrocardiogram basic signal u ⁇ ( ⁇ ) extracted by the rotation angle estimation unit 211 has an average value of 0 and a variance of Normalized to be 1.
  • the rotation angle estimation unit 211 estimates a pulsation period that is a period corresponding to the pulsation based on the extracted fetal electrocardiogram basic signal u ⁇ ( ⁇ ) for each pulsation of the heart of the fetus CB.
  • the rotation angle estimator 211 determines that the absolute value of the fetal electrocardiogram basic signal u ⁇ ( ⁇ ) (potential in this example) is smaller than a predetermined first threshold value. A certain point in time (for example, a point in the middle of the period) within the longer duration is estimated as the boundary point.
  • the rotation angle estimator 211 has a maximum peak time point that is a time point at which the value of the fetal electrocardiogram basic signal u ⁇ ( ⁇ ) is maximized in a period between two consecutive boundary time points among the estimated boundary time points. ⁇ max0 is acquired.
  • the rotational angle estimation unit 211 starting from just before the time half the time of pulsation cycle from the maximum peak point tau max0, and, from the maximum peak point tau max0 at a later time by half the time of pulsation cycles
  • the period that ends is estimated as the pulsation period.
  • the pulsation period may be obtained by obtaining an autocorrelation with respect to the fetal electrocardiogram basic signal u ⁇ ( ⁇ ). In this way, the rotation angle estimation unit 211 estimates the pulsation period for each pulsation of the heart of the fetus CB.
  • the rotation angle estimation unit 211 estimates the rotation angle ⁇ for each of the estimated pulsation periods.
  • the rotation angle estimation unit 211 holds in advance a relationship (first relationship) between the rotation angle and the signal feature amount.
  • the signal feature amount is a parameter calculated based on the maximum value and the minimum value of the fetal electrocardiogram basic signal in the QRS wave period that is a period corresponding to the QRS wave in the pulsation period.
  • the QRS wave is composed of a Q wave, an R wave, and an S wave.
  • the signal feature amount R ( ⁇ ) is expressed by Equation 2.
  • ⁇ max ( ⁇ ) represents a time point (QRS wave period maximum peak time point) in which the fetal electrocardiogram basic signal has a maximum value in the QRS wave period.
  • ⁇ min ( ⁇ ) represents a time point (QRS wave period minimum peak time point) in which the fetal electrocardiogram basic signal has a minimum value in the QRS wave period.
  • the QRS wave period is an example of a target period.
  • the QRS wave period maximum peak time ⁇ max ( ⁇ ) is expressed by Expression 3
  • the QRS wave period minimum peak time ⁇ min ( ⁇ ) is expressed by Expression 4.
  • T QRS represents the length of the QRS wave period.
  • T QRS is set to a value obtained by multiplying the pulsation period by a predetermined coefficient (for example, 1/5).
  • the first relationship is determined based on the reference signal (reference fetal electrocardiogram signal) of the fetal electrocardiogram signal expressed by Expressions 5 to 7.
  • ECG x0 ( ⁇ ) represents a reference fetal electrocardiogram signal when the fetus CB is viewed in the negative direction of the x-axis.
  • ECG y0 ( ⁇ ) represents a reference fetal electrocardiogram signal when the fetus CB is viewed in the negative direction of the y-axis.
  • ECG z0 ( ⁇ ) represents a reference fetal electrocardiogram signal when the fetus CB is viewed in the negative direction of the z-axis.
  • the reference fetal electrocardiogram signal is represented by the sum of Gaussian functions.
  • ⁇ i x , ⁇ i x , b i x , ⁇ i y , ⁇ i y , b i y , ⁇ i z , ⁇ i z , and b i z are parameters that specify a Gaussian function.
  • electrocardiogram signals described in “fetal ECG signals”, EURASIP Journal on Advances in Signal Processing, 2007, Article ID 43407) are used as reference fetal electrocardiogram signals.
  • the first relationship with the reference fetal electrocardiogram signal described above is determined as shown in FIG.
  • FIG. 9A the relationship between the rotation angle ⁇ and the QRS wave period maximum peak time point ⁇ max ( ⁇ ) is represented by a broken line, and the rotation angle ⁇ and the QRS wave period minimum peak time point ⁇ min ( ⁇ ).
  • the relationship between is represented by a solid line.
  • FIG. 9B the relationship between the rotation angle ⁇ and the signal feature amount R ( ⁇ ) is represented by a solid line.
  • np and a range of rotation angle ⁇ (maximum peak preceding range) ⁇ pn in which QRS wave period maximum peak time point ⁇ max ( ⁇ ) is smaller than QRS wave period minimum peak time point ⁇ min ( ⁇ ) exist.
  • the rotation angle ⁇ and the signal feature amount R ( ⁇ ) correspond one-to-one.
  • the rotation angle ⁇ and the signal feature amount R ( ⁇ ) correspond one-to-one.
  • the first relationship may be determined based on an empirical rule.
  • the rotation angle estimation unit 211 determines the QRS wave period maximum peak time point ⁇ max ( ⁇ ) and the QRS wave period minimum for each of the estimated pulsation periods based on the fetal electrocardiogram basic signal u ⁇ ( ⁇ ). The peak time ⁇ min ( ⁇ ) is acquired.
  • the rotation angle estimation unit 211 obtains the QRS wave period maximum peak time point ⁇ max ( ⁇ ) and the QRS wave period minimum peak time point ⁇ min ( ⁇ ) for each of the estimated pulsation periods. Then, a signal feature amount R ( ⁇ ) is calculated based on the fetal electrocardiogram basic signal u ⁇ ( ⁇ ).
  • the rotation angle estimation unit 211 determines the rotation angle ⁇ based on the first relationship held for each estimated pulsation period and the calculated signal feature R ( ⁇ ). Is estimated.
  • the rotation angle estimation unit 211 is held when the acquired QRS wave period maximum peak time ⁇ max ( ⁇ ) is larger than the acquired QRS wave period minimum peak time ⁇ min ( ⁇ ).
  • the rotation angle ⁇ is estimated based on the portion corresponding to the minimum peak preceding range ⁇ np and the calculated signal feature amount R ( ⁇ ) in the first relationship.
  • the rotation angle estimation unit 211 holds the first QRS wave period maximum peak time point ⁇ max ( ⁇ ) that is held when the acquired QRS wave period minimum peak time point ⁇ min ( ⁇ ) is smaller than the acquired QRS wave period minimum peak time point ⁇ min ( ⁇ ).
  • the rotation angle ⁇ is estimated based on the portion corresponding to the maximum peak preceding range ⁇ pn and the calculated signal feature amount R ( ⁇ ). In this way, the rotation angle estimation unit 211 estimates the rotation angle ⁇ for each pulsation period.
  • the maximum peak time ⁇ max0 in the fetal electrocardiogram basic signal changes according to the rotation angle ⁇ .
  • a dashed curve C20 represents a reference fetal electrocardiogram signal when the rotation angle is 0 (when the fetus CB is viewed in the negative direction of the x axis), and a solid curve C21 represents the rotation angle.
  • the reference fetal electrocardiogram signal when the value is different from 0 is represented.
  • the electrocardiogram signal estimation unit 212 estimates again the time point that is the center of the pulsation period for each of the estimated pulsation periods based on the rotation angle ⁇ estimated by the rotation angle estimation unit 211.
  • the pulsation period is estimated again based on the re-estimated time.
  • a dotted curve C22 is a curve obtained by translating the curve C21 on the time axis by the correction amount at the time point that is the center of the pulsation period.
  • the electrocardiogram signal estimation unit 212 holds in advance a relationship (second relationship) between the rotation angle and the maximum peak time point change rate.
  • the maximum peak time point change rate includes the QRS wave period maximum peak time point ⁇ max ( ⁇ ) when the rotation angle is ⁇ and the QRS wave period maximum peak time point ⁇ max (0 when the rotation angle is 0. ) And the parameters calculated based on the above.
  • the maximum peak time point change rate S ( ⁇ ) is expressed by Equation 8.
  • the second relationship is determined based on the reference fetal electrocardiogram signal expressed by the above formulas 5 to 7. Therefore, the second relationship is determined as shown in FIG. Note that the second relationship may be determined based on an empirical rule.
  • the electrocardiogram signal estimation unit 212 determines the rotation angle ⁇ estimated by the rotation angle estimation unit 211 and the second relationship held for each of the pulsation periods estimated by the rotation angle estimation unit 211. Based on this, the maximum peak time point change rate S ( ⁇ ) is acquired.
  • the electrocardiogram signal estimation unit 212 rotates based on the acquired maximum peak time point change rate S ( ⁇ ) and Equation 9 for each of the pulsation periods estimated by the rotation angle estimation unit 211.
  • the QRS wave period maximum peak time point ⁇ max (0) when the angle is 0 is calculated.
  • the QRS wave period maximum peak time point ⁇ max (0) is an example of the maximum value time point.
  • the electrocardiogram signal estimation unit 212 uses the calculated QRS wave period maximum peak time point ⁇ max (0) for each of the pulsation periods estimated by the rotation angle estimation unit 211 as the center of the pulsation period. Estimate as In this manner, the electrocardiogram signal estimation unit 212 re-estimates the time point that is the center of the pulsation period.
  • the electrocardiogram signal estimation unit 212 has a time point that is half the time of the pulsation period before the QRS wave period maximum peak time point ⁇ max (0) with respect to each of the pulsation periods estimated by the rotation angle estimation unit 211. And a period that ends at a time point half the pulsation period after the QRS wave period maximum peak time ⁇ max (0) is re-estimated as a pulsation period.
  • the electrocardiogram signal estimation unit 212 determines the fetal CB for a predetermined reference rotation angle based on the re-estimated pulsation period, the rotation angle ⁇ estimated by the rotation angle estimation unit 211, and the fetal electrocardiogram basic signal. An electrocardiogram signal (fetal electrocardiogram signal) is estimated.
  • the electrocardiogram signal estimation unit 212 uses the first fetal electrocardiogram signal ECG x ( ⁇ ) when the rotation angle is 0 and the second fetal electrocardiogram signal ECG y when the rotation angle is 3 ⁇ / 2. ( ⁇ ) is estimated.
  • the first fetal electrocardiogram signal ECG x ( ⁇ ) is an example of an electrocardiogram signal of the fetus CB with respect to 0 as the first reference rotation angle.
  • the second fetal electrocardiogram signal ECG y ( ⁇ ) is an example of an electrocardiogram signal of the fetus CB with respect to 3 ⁇ / 2 as the second reference rotation angle.
  • p signal values included in each of the re-estimated pulsation periods can be interpreted as p-dimensional vectors.
  • p represents a natural number and is also called a sample number.
  • the p signal values included in each of the plurality of beat periods are represented by one point in the p-dimensional space. Therefore, the fetal electrocardiogram basic signal forms a set of points in the p-dimensional space that is the same as the number of pulsation periods included in the fetal electrocardiogram basic signal.
  • the electrocardiogram signal estimation unit 212 performs the principal component analysis on the set of points representing the fetal electrocardiogram basic signal in the p-dimensional space, so that the first principal component vector and the second component orthogonal to each other are obtained. Get the principal component vector of.
  • the electrocardiogram signal estimation unit 212 for each re-estimated pulsation period, of the first principal component u ⁇ 1 and the second principal component u ⁇ 2 of the fetal electrocardiogram basic signal in the pulsation period.
  • the first principal component u ⁇ 1 is a component in the direction along the first principal component vector in the fetal electrocardiogram basic signal in the pulsation period.
  • the second principal component u ⁇ 2 is a component in the direction along the second principal component vector in the fetal electrocardiogram basic signal in the pulsation period.
  • the electrocardiogram signal estimation unit 212 estimates a first rotation angle ⁇ 1 corresponding to the first principal component vector and a second rotation angle ⁇ 2 corresponding to the second principal component vector.
  • the electrocardiogram signal estimation unit 212 calculates the QRS wave period maximum peak time point ⁇ max ( ⁇ ) and the QRS wave period minimum peak time point ⁇ min ( ⁇ ) for the signal represented by the first principal component vector.
  • the signal feature amount R ( ⁇ ) is calculated based on the QRS wave period maximum peak time ⁇ max ( ⁇ ) and the QRS wave period minimum peak time ⁇ min ( ⁇ ).
  • the electrocardiogram signal estimation unit 212 estimates the first rotation angle ⁇ 1 based on the held first relationship and the calculated signal feature amount R ( ⁇ ).
  • the electrocardiogram signal estimation unit 212 estimates the second rotation angle ⁇ 2 with respect to the signal represented by the second principal component vector.
  • the electrocardiogram signal estimation unit 212 performs scaling based on Equation 10 and Equation 11.
  • E [X] represents the average of X.
  • V [X] represents the variance of X.
  • ECG [theta] 10 represents the reference fetal electrocardiogram signal when viewed fetal CB negative direction of the x-axis the first rotation angle theta 1 only toward the rotated direction.
  • ECG? 20 represents a reference fetal electrocardiogram signal when viewed fetal CB negative direction of the x-axis the second rotation angle theta 2 only toward the rotated direction.
  • the electrocardiogram signal estimation unit 212 has the first principal component ECG ⁇ 1 and the second principal component ECG ⁇ 2 after scaling, the estimated first rotation angle ⁇ 1 and second rotation angle ⁇ 2 , , The first fetal electrocardiogram signal ECG x ( ⁇ ) and the second fetal electrocardiogram signal ECG y ( ⁇ ) are estimated.
  • the electrocardiogram signal estimation unit 212 generates a vector electrocardiogram based on the estimated first fetal electrocardiogram signal ECG x ( ⁇ ) and the estimated second fetal electrocardiogram signal ECG y ( ⁇ ). May be.
  • the information acquisition unit 220 acquires biological state information representing the state of the fetus CB based on the first fetal electrocardiogram signal ECG x ( ⁇ ) estimated by the electrocardiogram signal estimation unit 212.
  • the information acquisition unit 220 instead of the first fetal electrocardiogram signal ECG x ( ⁇ ), or, in addition to the first fetal electrocardiogram signal ECG x ( ⁇ ), a second fetal electrocardiogram signal ECG y (tau ) To obtain biological state information.
  • the information acquisition unit 220 acquires an RR interval that is a time interval between peaks of consecutive R waves in the first fetal electrocardiogram signal ECG x ( ⁇ ).
  • the RR interval is a time interval between a certain R wave peak and an R wave peak following the R wave.
  • the R wave is an example of a reference wave
  • the RR interval is an example of a reference wave interval.
  • the information acquisition unit 220 acquires each RR interval included in the acquisition period for each of a plurality of different acquisition periods.
  • the length of each acquisition period is set such that the number of RR intervals included in the acquisition period is a number within a predetermined range (for example, a range from 300 to 400, etc.).
  • the length of each predetermined period may be a predetermined acquisition time (for example, 1 minute, 5 minutes, 10 minutes, etc.). In this case, the length of the acquisition period may be constant. Note that the length of the acquisition period may be different for each acquisition period.
  • the plurality of acquisition periods are set such that a part of each of the plurality of acquisition periods overlaps a part of another acquisition period.
  • the plurality of acquisition periods start at a time after each acquisition period by a predetermined offset time (in this example, a time corresponding to 100 heart rates) from the time when the immediately preceding acquisition period starts. Set to do.
  • the heart rate is the number of times the heart of the fetus CB beats.
  • the plurality of acquisition periods may be set such that a predetermined non-acquisition period is provided between each acquisition period and the acquisition period immediately after the acquisition period.
  • the length of the non-acquisition period may be constant. Note that the length of the non-acquisition period may be different for each non-acquisition period.
  • FIG. 12 is a graph showing an example of a change in the RR interval with respect to the heart rate.
  • the information acquisition unit 220 acquires, for each of a plurality of acquisition periods, a frequency distribution representing the frequency with which the RR interval included in the class range exists for each class range based on the acquired RR interval.
  • the information acquisition unit 220 sets a plurality of class ranges obtained by dividing the distribution range including the acquired RR interval.
  • the width of the class range is constant. Note that the width of the class range may be different for each class range.
  • the information acquisition unit 220 acquires the frequency distribution by counting the number of RR intervals included in the class range for each of the plurality of acquisition periods.
  • the information acquisition unit 220 acquires a normalized frequency distribution based on the acquired frequency distribution for each of a plurality of acquisition periods.
  • the normalized frequency distribution is a frequency distribution normalized so that the sum of products of the width of the class range and the frequency for the class range is 1.
  • FIG. 13 is a graph showing an example of the normalized frequency distribution with respect to the RR interval of the fetus CB at the 23rd week of pregnancy.
  • a rectangle FD1 indicated by hatching indicates an example of a normalized frequency distribution when the state of the fetus CB is normal.
  • a rectangle FD2 indicated by cross hatching represents an example of a normalized frequency distribution when the state of the fetus CB is abnormal.
  • the information acquisition unit 220 acquires a function specifying parameter for specifying a predetermined function representing a probability distribution with respect to the RR interval based on the acquired normalized frequency distribution for each of a plurality of acquisition periods.
  • the predetermined function representing the probability distribution is a probability density function.
  • this function is a probability density function g ⁇ (z) that represents a general extreme value distribution, which is expressed by Expressions 13 to 15.
  • z represents the RR interval as a random variable.
  • ⁇ represents a position parameter
  • ⁇ represents a scale parameter
  • ⁇ represents a shape parameter.
  • the position parameter ⁇ , the scale parameter ⁇ , and the shape parameter ⁇ are examples of function specifying parameters.
  • Equation 13 represents the probability density function g ⁇ (z) when the shape parameter ⁇ is not 0 and the random variable z satisfies the condition represented by Equation 14.
  • Equation 15 represents the probability density function g ⁇ (z) when the shape parameter ⁇ is zero.
  • the probability distribution for the RR interval is well represented by the general extreme value distribution. Therefore, the shape parameter ⁇ of the general extreme value distribution represents the state of the fetus CB with high accuracy. For this reason, according to the fetal state estimation device 1 according to the first embodiment, information representing the state of the fetus CB with high accuracy can be acquired.
  • the shape parameter ⁇ is an example of biological state information.
  • the biological state information may be any one of the position parameter ⁇ , the scale parameter ⁇ , and the shape parameter ⁇ , or any combination thereof.
  • the information acquisition unit 220 estimates the function specifying parameter by using the maximum likelihood method.
  • the information acquisition unit 220 may estimate the function specifying parameter by using a method different from the maximum likelihood method such as the least square method.
  • a solid curve PDF1 represents the probability density function g ⁇ (z) specified by the function specifying parameter acquired for the normalized frequency distribution FD1 when the state of the fetus CB is normal.
  • a dotted curve PDF2 represents the probability density function g ⁇ (z) specified by the function specifying parameter acquired for the normalized frequency distribution FD2 when the state of the fetus CB is abnormal. .
  • FIG. 14 is a graph showing an example of the shape parameter ⁇ for each of a plurality of acquisition periods when the state of the fetus CB at 23 weeks of pregnancy is normal.
  • FIG. 15 is a graph showing an example of the shape parameter ⁇ for each of a plurality of acquisition periods when the state of the fetus CB at the 23rd week of pregnancy is abnormal.
  • the biological state determination unit 230 determines that the state of the fetus CB is abnormal when the shape parameter ⁇ acquired by the information acquisition unit 220 has a positive value. On the other hand, the biological state determination unit 230 determines that the state of the fetus CB is normal when the shape parameter ⁇ acquired by the information acquisition unit 220 has a negative value.
  • the biological state determination unit 230 determines that the state of the fetus CB is abnormal when the shape parameter ⁇ is equal to or greater than a predetermined positive determination threshold (for example, 0.1), and the shape parameter ⁇ is greater than the determination threshold. May be determined that the state of the fetus CB is normal.
  • a predetermined positive determination threshold for example, 0.1
  • the biological state determination unit 230 also determines the frequency with which the shape parameter ⁇ has a positive value, the number of consecutive acquisition periods in which the shape parameter ⁇ has a positive value, the average value of the shape parameter ⁇ , or the variance of the shape parameter ⁇ . May be determined that the condition of the fetus CB is abnormal.
  • the biological state determination unit 230 may determine whether or not the state of the fetus CB is normal based on information entropy with respect to the time series data of the shape parameter ⁇ . For example, the biological state determination unit 230 uses the shape parameters ⁇ 0 , ⁇ 1 ,..., ⁇ m for each of the m acquisition periods and the m time-series data ⁇ 0 , ⁇ 1 ,. The information entropy H for the m pieces of time series data ⁇ 0 , ⁇ 1 ,..., ⁇ m of the shape parameter ⁇ may be calculated based on Expression 16. m represents an integer of 2 or more.
  • the biological state determination unit 230 calculates information entropy every time the shape parameter ⁇ is newly acquired. Furthermore, the biological state determination unit 230 determines that the state of the fetus CB is abnormal when the calculated information entropy is larger than a previously calculated value by a predetermined increase threshold (for example, 0). judge.
  • a predetermined increase threshold for example, 0
  • the biological state determination unit 230 may determine whether or not the state of the mother MB is normal instead of the state of the fetus CB or in addition to the state of the fetus CB.
  • the output unit 30 outputs information representing the determination result by the biological state determination unit 230.
  • the output unit 30 may output (for example, display on a display) information (for example, a graph) indicating a change with respect to time of the biological state information acquired by the information acquisition unit 220.
  • the output unit 30 may store the information in a storage device in addition to the information output or instead of the information output.
  • each electrode 11-15 is attached to the surface (eg skin) MBS of the abdomen of the maternal MB during pregnancy.
  • the fetal state estimation device 1 extracts a fetal electrocardiogram basic signal from the bioelectric potential signal measured by the measurement unit 10 by using an independent component analysis method (step S101 in FIG. 16). Next, the fetal state estimation device 1 estimates the boundary time point, and the value of the fetal electrocardiogram basic signal u ⁇ ( ⁇ ) is maximized in the period between two consecutive boundary time points among the estimated boundary time points. The maximum peak time point ⁇ max0 that is the time point is acquired (step S102 in FIG. 16).
  • fetal state estimating device 1 starts only from a previous point in time half the time of pulsation cycle from the maximum peak point tau max0, and, from the maximum peak point tau max0 at a later time by half the time of pulsation cycles The period that ends is estimated as the pulsation period (step S103 in FIG. 16).
  • the fetal state estimation device 1 acquires the QRS wave period maximum peak time point ⁇ max ( ⁇ ) and the QRS wave period minimum peak time point ⁇ min ( ⁇ ) for each of the estimated pulsation periods. The fetal state estimation device 1 then obtains the QRS wave period maximum peak time point ⁇ max ( ⁇ ) and the QRS wave period minimum peak time point ⁇ min ( ⁇ ) for each of the estimated pulsation periods. Then, a signal feature amount R ( ⁇ ) is calculated based on the fetal electrocardiogram basic signal u ⁇ ( ⁇ ) (step S104 in FIG. 16).
  • the fetal state estimation device 1 calculates the rotation angle ⁇ based on the first relationship held for each estimated pulsation period and the calculated signal feature R ( ⁇ ). Estimation is performed (step S105 in FIG. 16).
  • the fetal state estimation device 1 determines the maximum peak time point change rate S ( ⁇ ) based on the estimated rotation angle ⁇ and the held second relationship for each of the estimated pulsation periods. ) To get. Furthermore, the fetal state estimation device 1 uses the QRS wave period maximum peak when the rotation angle is 0 based on the acquired maximum peak time point change rate S ( ⁇ ) for each of the estimated pulsation periods. The time ⁇ max (0) is calculated. Next, the fetal state estimation device 1 estimates the calculated QRS wave period maximum peak time point ⁇ max (0) as the time point that is the center of the pulsation period (step S106 in FIG. 16).
  • the fetal state estimation device 1 starts from a time point that is half the pulsation period before the QRS wave period maximum peak time point ⁇ max (0) for each estimated pulsation period, and A period ending at a time point after half the pulsation period from the QRS wave period maximum peak time point ⁇ max (0) is estimated again as a pulsation period (step S107 in FIG. 16).
  • the fetal state estimation device 1 estimates a fetal electrocardiogram signal with respect to the reference rotation angle based on the re-estimated pulsation period, the estimated rotation angle ⁇ , and the extracted fetal electrocardiogram basic signal ( Step S108 in FIG.
  • the fetal state estimation device 1 estimates the first fetal electrocardiogram signal with respect to the first reference rotation angle and the second fetal electrocardiogram signal with respect to the second reference rotation angle.
  • the fetal state estimation device 1 acquires an RR interval for each of a plurality of acquisition periods based on the estimated first fetal electrocardiogram signal. Next, the fetal state estimation device 1 acquires a frequency distribution with respect to the RR interval based on the acquired RR interval for each of the plurality of acquisition periods. Further, the fetal state estimation device 1 acquires a normalized frequency distribution based on the acquired frequency distribution for each of a plurality of acquisition periods (step S109 in FIG. 16).
  • the fetal state estimation device 1 acquires a function specifying parameter based on the acquired normalized frequency distribution for each of a plurality of acquisition periods (step S110 in FIG. 16). Then, the fetal state estimation device 1 determines whether or not the state of the fetus CB is normal based on the acquired function specifying parameter (step S111 in FIG. 16).
  • the fetal state estimation device 1 uses, as information representing the state of the fetus CB, the parameter that specifies the probability density function representing the probability distribution with respect to the RR interval in the acquired electrocardiogram signal. get. According to this, information representing the state of the fetus CB with high accuracy can be acquired.
  • the fetal state estimation device 1 rotates the fetus CB with respect to the maternal MB of the fetus CB for each heart beat based on a bioelectric potential signal representing a change in potential on the surface MBS of the maternal MB. Estimate the angle. In addition, the fetal state estimation device 1 estimates an electrocardiogram signal with respect to a predetermined reference rotation angle based on the bioelectric potential signal and the estimated rotation angle.
  • the manner in which the change in the electromotive force of the fetus CB appears depends on the rotation angle of the fetus CB with respect to the mother MB. Therefore, according to the fetal state estimation device 1 according to the first embodiment, it is possible to acquire an electrocardiogram signal in which the variation of the aspect in which the change in the electromotive force of the fetus CB appears in the electrocardiogram signal is suppressed. As a result, information representing the state of the fetus CB with high accuracy can be acquired.
  • the fetal state estimation device 1 estimates an electrocardiogram basic signal caused by the heart beat of the fetus CB. Further, the fetal state estimation device 1 calculates a predetermined signal feature amount based on the maximum value and the minimum value in a predetermined target period of the estimated electrocardiogram basic signal for each heart beat of the fetus CB. In addition, the fetal state estimation device 1 estimates the rotation angle based on the calculated signal feature amount for each heart beat of the fetus CB.
  • the relationship between the maximum value and the minimum value of the electrocardiogram basic signal in a predetermined target period for each heart beat of the fetus CB well represents the rotation angle of the fetus CB with respect to the mother MB. Therefore, according to the fetal state estimation device 1 according to the first embodiment, the rotation angle of the fetus CB with respect to the mother MB can be estimated with high accuracy.
  • the fetal state estimation device 1 includes, for each heartbeat of the fetus CB, the estimated ECG basic signal having the maximum value in the target period and the estimated rotation angle. Based on this, a maximum value time point, which is a time point when the electrocardiogram signal with respect to a predetermined reference rotation angle has a maximum value, is estimated. In addition, the fetal state estimation device 1 estimates an electrocardiogram signal based on the estimated maximum time point, the estimated rotation angle, and the estimated electrocardiogram basic signal.
  • the manner in which the change in the electromotive force of the fetus CB appears varies depending on the rotation angle of the fetus CB with respect to the mother MB. Therefore, according to the fetal state estimation device 1 according to the first embodiment, it is possible to estimate the maximum time point at which the electrocardiogram signal has the maximum value for each heart beat of the fetus CB with high accuracy. As a result, the electrocardiogram signal can be estimated with high accuracy based on the estimated maximum value time point. Therefore, information representing the state of the fetus CB with high accuracy can be acquired.
  • the fetal state estimation device 1 estimates an electrocardiogram basic signal by an independent component analysis method. According to this, the electrocardiogram basic signal can be estimated with high accuracy.
  • the fetal state estimation device 1 may be used for a fetus CB in a week before the 23rd week of pregnancy or a week after the 23rd week of pregnancy. Moreover, although the fetal state estimation apparatus 1 has acquired biological state information based on an electrocardiogram signal with respect to a predetermined reference rotation angle, the fetal state estimation device 1 may acquire biological state information based on an electrocardiogram basic signal.
  • the fetal state estimation apparatus 1 was used for the fetus CB.
  • the biological condition estimation apparatus according to the present invention may be used for a human after birth (newborn, infant, infant, child, adult, etc.).
  • the biological state estimation apparatus acquires an electrocardiogram signal using a known method such as a 12-lead electrocardiogram and acquires biological state information based on the acquired electrocardiogram signal.
  • the fetal state estimation device 1 uses a probability density function representing a general extreme value distribution as a predetermined function representing a probability distribution, but other probability distributions such as a negative hypergeometric distribution (beta binomial distribution).
  • a probability density function that represents may be used.
  • the predetermined function representing the probability distribution is a probability density function g ⁇ (z) representing the beta binomial distribution represented by Expression 17 and Expression 18.
  • z represents the RR interval as a random variable.
  • ⁇ (a, b) represents a beta function
  • a represents a first parameter
  • b represents a second parameter.
  • the first parameter a and the second parameter b are examples of function specifying parameters.
  • Equation 17 represents the probability density function g ⁇ (z) when the random variable z satisfies the condition represented by Equation 18.
  • the probability density function g ⁇ (z) is zero.
  • the probability distribution for the RR interval is well represented by the beta binomial distribution. Therefore, the first parameter a and the second parameter b of the beta binomial distribution represent the state of the fetus CB with high accuracy. For this reason, the fetal state estimation apparatus 1 according to this modification can also acquire information representing the state of the fetus CB with high accuracy.
  • the first parameter a and the second parameter b are examples of biological state information.
  • the fetal state estimation device 1 determines that the state of the fetus CB is abnormal when the value a / b obtained by dividing the first parameter a by the second parameter b is smaller than 1.
  • the fetal state estimation device 1 determines that the state of the fetus CB is normal.
  • the biological state information may be any one of the first parameter a and the second parameter b.
  • the fetal state estimation device 1 uses the general extreme value distribution for the fetus CB from the 20th to the 27th week of pregnancy and the beta binomial distribution for the fetus CB after the 28th week of pregnancy. May be.
  • the autonomic nervous system develops after the 28th week of pregnancy.
  • the fetal state estimation device 1 may not include the biological state determination unit 230 as a function. In this case, it is preferable that the fetal state estimation device 1 outputs (for example, displays on a display) information (for example, a graph) indicating changes with respect to time of the biological state information acquired by the information acquisition unit 220.
  • the fetal state estimation device 1 outputs (for example, displays on a display) information (for example, a graph) indicating changes with respect to time of the biological state information acquired by the information acquisition unit 220.

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Abstract

Un dispositif (1) d'estimation d'état corporel acquiert des données indiquant un état corporel. Le dispositif (1) d'estimation d'état corporel comprend : une unité d'acquisition de signal d'électrocardiogramme, qui acquiert un signal d'électrocardiogramme du corps ; et une unité d'acquisition de données, qui acquiert en tant que données un paramètre spécifiant une fonction prescrite, laquelle représente une distribution de probabilités par rapport à un intervalle d'onde de référence, qui constitue un intervalle de temps entre des pics d'ondes de référence prescrites successives dans le signal d'électrocardiogramme acquis.
PCT/JP2014/058589 2014-03-26 2014-03-26 Dispositif, procede et programme d'estimation d'etat corporel WO2015145625A1 (fr)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20210015306A (ko) * 2019-08-01 2021-02-10 성균관대학교산학협력단 클래스 확률 출력망 기반 심장 상태 분류 방법 및 장치

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6359084B2 (ja) * 2014-03-26 2018-07-18 国立大学法人東北大学 生体状態推定装置、生体状態推定装置の作動方法、及び、生体状態推定プログラム

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS59120135A (ja) * 1982-12-28 1984-07-11 株式会社東芝 心機能診断装置
US20060074329A1 (en) * 2003-02-12 2006-04-06 Ferguson James E Ii Quantitative fetal heart rate and cardiotocographic monitoring system and related method thereof
US20100185108A1 (en) * 2007-07-20 2010-07-22 Vullings Rik Fetal monitoring
US20110092837A1 (en) * 2009-10-21 2011-04-21 Industrial Technology Research Institute Apparatus and method for monitoring fetus in maternal body

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5596993A (en) * 1994-09-21 1997-01-28 Beth Israel Hospital Fetal data processing system and method
US6804551B2 (en) 1998-03-17 2004-10-12 University Of Virginia Patent Foundation Method and apparatus for the early diagnosis of subacute, potentially catastrophic illness
GB0123772D0 (en) * 2001-10-03 2001-11-21 Qinetiq Ltd Apparatus for monitoring fetal heartbeat
US7333850B2 (en) * 2004-05-28 2008-02-19 University Of Florida Research Foundation, Inc. Maternal-fetal monitoring system
JP4590554B2 (ja) 2005-01-31 2010-12-01 国立大学法人東北大学 心電図信号処理方法および心電図信号処理装置
JP6359084B2 (ja) * 2014-03-26 2018-07-18 国立大学法人東北大学 生体状態推定装置、生体状態推定装置の作動方法、及び、生体状態推定プログラム

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPS59120135A (ja) * 1982-12-28 1984-07-11 株式会社東芝 心機能診断装置
US20060074329A1 (en) * 2003-02-12 2006-04-06 Ferguson James E Ii Quantitative fetal heart rate and cardiotocographic monitoring system and related method thereof
US20100185108A1 (en) * 2007-07-20 2010-07-22 Vullings Rik Fetal monitoring
US20110092837A1 (en) * 2009-10-21 2011-04-21 Industrial Technology Research Institute Apparatus and method for monitoring fetus in maternal body

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20210015306A (ko) * 2019-08-01 2021-02-10 성균관대학교산학협력단 클래스 확률 출력망 기반 심장 상태 분류 방법 및 장치
KR102264569B1 (ko) 2019-08-01 2021-06-15 성균관대학교산학협력단 클래스 확률 출력망 기반 심장 상태 분류 방법 및 장치

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